This report is focused around Lost and Found data using the intakes and outcomes data received for 2020 and 2021. Its goal is to reflect everything we could learn about L&F from the available data, make sure the numbers we see make sense, and highlight things that would be useful to show but some/all data required for them are missing.
Scroll down or use the table of contents on the left to navigate throughout the document. Most sections contain multiple tabs showing different facets of a data type. Most plots are interactive, meaning they include tooltips and allow hiding and showing parts and zooming in and out. If something went wrong, look for the house icon in the top right corner of each figure to reset.
This section provides an overview of the RTH rate per year divided by species. RTH Rate is calculated as the portion of returned animals that came in as strays out of stray animals.
CCP and TNR cats were excluded (based on the intake subtype field), and all animals in the age group Unweaned were excluded as well.
| Species | Year | Strays | RTH_Count | RTH_Rate |
|---|---|---|---|---|
| Cat | 2020 | 312 | 5 | 1.6% |
| Cat | 2021 | 581 | 13 | 2.24% |
| Cat | 2022 | 87 | 1 | 1.15% |
| Dog | 2020 | 715 | 232 | 32.45% |
| Dog | 2021 | 2582 | 848 | 32.84% |
| Dog | 2022 | 403 | 121 | 30.02% |
| Other | 2021 | 57 | 5 | 8.77% |
This section breaks dog RTH rate by the most common intake subtypes.
While Law Enforcement intakes are expected to be higher (known owner), it is interesting to note that field intakes (ACO) have higher RTH rates than public drop offs across all three years.
These three time series show the RTH rate per month, to show whether there were times with particularly high or low rates as well as the overall trajectory.
The RTH rate is fairly stable (which is positive in light of the increasing intake volume seen below), with a small dip around November-December of both 2020 and 2021. This is fairly atypical, as many other shelters actually show higher RTH rates around the turn of the year.
This section shows the number of stray intakes over time, as well as the breakdown of strays by field/shelter intake.
This could be another useful metrics to reflect the benefits of RTH over other outcome types. It takes into account three components:
As an example, there were 848 stray dos who got RTH in 2021. Assuming 30$ cost of daily care per dog, and given the length-of-stay differences, We can estimate that return-to-homes for dogs saved CAC \(848*30*29=\$737,760\) in costs of care.
Of course, that is a pretty basic calculation that is meant to demonstrate the difference between these outcomes, even if the budget did not actually change by this amount as a result of achieving RTH outcomes.
Data Note: the length of stay seems higher than average – does this surpise you? In case the averages were high because of a few outliers we looked at the median, but it too is higher than usual.
| Species | Outcome | Count | Average_Length_Of_Stay | Median_Length_Of_Stay |
|---|---|---|---|---|
| Cat | Other Outcomes | 622 | 51.72 | 40 |
| Cat | RTO | 19 | 1.37 | 1 |
| Dog | Other Outcomes | 1937 | 41.64 | 29 |
| Dog | RTO | 1201 | 1.83 | 1 |
The following maps show stray intake and RTH rate by Census tracts to highlight geographical patterns. The first and second tab are similar to previous metrics; the third tab, RTH Gap, shows the number of strays who were not returned home per Census tract
The data in this section includes stray dogs for which found addresses were present and workable, meaning they had a street number or an intersection (as opposed to just a street name). Unfortunately, out of ~6000 stray animals, after removing ~150 with the shelter address, there were 1000 additional animals with address that could not be mapped. This was primarily due to only using a street name rather than a name and number or an intersection.
After this filtering, the data below (number of strays, rate of RTH, RTH gap) is shown for 2932 stray dogs of which 991 were RTHs. The next section maps 1819 cats.
Generally speaking, lower-intake areas have higher rates here, which is similar to other communities.
This combines the other two tabs to highlight where most additional RTH potential exists. Since RTH rates were generally higher in lower intake areas, the gaps highlight the same areas shown in the stray intake map and driven primarily by higher intake volumes than a particularly low RTH rate in a given area.
Here’s a sneak peak into the top 10 found locations plotted above, to make sure they make sense to you.
| Found.Location | Count |
|---|---|
| 4701 Montgomery Road Norwood OH | 15 |
| 10245 Winton Road Springfield Township OH | 14 |
| 1130 Compton Road Springfield Township OH | 10 |
| 1203 West Kemper Road Forest Park OH | 9 |
| 22 Poplar Street Elmwood Place OH | 8 |
| 3964 Red Bank Road Fairfax OH | 8 |
| 4725 Springdale Road Colerain Township OH | 8 |
| Hamilton Avenue and Galbraith Road Mt. Healthy OH | 8 |
| 5083 Colerain Avenue Mt. Airy OH | 7 |
| 600 Grove Avenue Wyoming OH | 7 |
This is similar to the stray intake map above, but for 1819 stray cats. Since only 96 of those were RTH, there is no point in mapping those across town.
Here’s a sneak peak into the top 10 found locations plotted above, to make sure they make sense to you.
| Found.Location | Count |
|---|---|
| 4549 Schinkal Road Miami Heights OH | 30 |
| 4346 Vine Street St. Bernard OH | 13 |
| 1115 Rosemont Avenue Price Hill OH | 11 |
| 170 Richardson Place Saylor Park OH | 8 |
| 227 Country Trace Avenue Harrison OH | 8 |
| 310 South State Street Harrison OH | 8 |
| 54 Euclid Avenue Wyoming OH | 8 |
| Rose Lane and Glensprings Drive Springdale OH | 8 |
| 1413 Bellwood Drive Loveland OH | 7 |
| 2760 West Galbraith Road Colerain Township OH | 7 |
This map shows different demogrpahic information for Hamilton County.
Found location was missing or non-usuable (primarily because only a street name was inserted -- Hoffner street, Harrison, Hamilton, Madison, Reading Road -- without a number or an intersection) for about 1000 out of 6000 stray intakes. If ZIP codes are tracked more regularly, we could use them as well (they are not in the data we got so far), but for a map based on exact locations the main solution is improving data entry.
Intake subtype for strays has multiple values assigned to less than 20 animals, which could be removed to simplify or thought through again. It seems like a lot of information is condensed into it, e.g. an indication of TNR/CCP and a specificity of ‘TNR with Cat Has Microchip’.
We were not sure how to count the Law Enforcement category under stray, which we would usually classify as ‘seizure/confiscate’ as opposed to stray.
Other things we could show if we had the data for it:
Thanks for reading through, and we’re looking forward to talking through it and thinking about more ways to make this data useful for you.